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Learning control variables and instruments for causal analysis in observational data

This study introduces a data-driven, machine learning-based method to detect suitable control variables and instruments for assessing the causal effect of a treatment on an outcome in observational data, if they exist. Our approach tests the joint existence of instruments, which are associated with the treatment but not directly with...

Presented by: Nicolas Apfel (University of Innsbruck)

Venue: Online